NDLI: Mining interesting user behavior patterns in mobile commerce environments

Content Provider	Springer Nature Link
Author	Shie, Bai En Yu, Philip S. Tseng, Vincent S.
Copyright Year	2012
Abstract	Discovering user behavior patterns from mobile commerce environments is an essential topic with wide applications, such as planning physical shopping sites, maintaining e-commerce on mobile devices and managing online shopping websites. Mobile sequential pattern mining is an emerging issue in this topic, which considers users’ moving paths and purchased items in mobile commerce environments to find the complete set of mobile sequential patterns. However, an important factor, namely users’ interests, has not been considered yet in past studies. In practical applications, users may only be interested in the patterns with some user-specified constraints. The traditional methods without considering the constraints pose two crucial problems: (1) Users may need to filter out uninteresting patterns within huge amount of patterns, (2) Finding the complete set of patterns containing the uninteresting ones needs high computational cost and runtime. In this paper, we address the problem of mining mobile sequential patterns with two kinds of constraints, namely importance constraints and pattern constraints. Here, we consider the importance of an item as its utility (i.e., profit) in the mobile commerce environment. An efficient algorithm, IM-Span (I nteresting M obile S equential Pa tter n mining), is proposed for dealing with the two kinds of constraints. Several effective strategies are employed to reduce the search space and computational cost in different aspects. Experimental results show that the proposed algorithms outperform state-of-the-art algorithms significantly under various conditions.
Starting Page	418
Ending Page	435
Page Count	18
File Format	PDF
ISSN	0924669X
Journal	Applied Intelligence
Volume Number	38
Issue Number	3
e-ISSN	15737497
Language	English
Publisher	Springer US
Publisher Date	2012-09-07
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Interesting pattern discovery Mobility pattern mining Utility mining Mobile commerce environment User constraints Artificial Intelligence (incl. Robotics) Mechanical Engineering Manufacturing, Machines, Tools
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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